code: def test_smoke(self, num_points, device, dtype):
      intrinsics, _, world_points, img_points = self._get_test_data(
          num_points, device, dtype
      )
      batch_size = world_points.shape[0]
  
      pred_world_to_cam = kornia.geometry.solve_pnp_dlt(
          world_points, img_points, intrinsics
      )
      assert pred_world_to_cam.shape == (batch_size, 3, 4)
  
file_path: kornia/test/geometry/calibration/test_pnp.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  from kornia.geometry.calibration.pnp import _mean_isotropic_scale_normalize
  from kornia.testing import assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestSolvePnpDlt obj's underlying member method code with example usage: obj.test_smoke(num_points, device, dtype) without return types